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A support vector machine model for pipe crack size classificationMiao, Chuxiong. January 2009 (has links)
Thesis (M. Sc.)--University of Alberta, 2009. / Title from pdf file main screen (viewed on July 16, 2009). "A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Master of Science, Department of Mechanical Engineering, University of Alberta." Includes bibliographical references.
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Analysis and design of cryptographic hash functionsKasselman, Pieter Retief 20 December 2006 (has links)
Please read the abstract in the section 00front of this document. / Dissertation (M Eng (Electronic Engineering))--University of Pretoria, 2006. / Electrical, Electronic and Computer Engineering / unrestricted
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Impact of speed variations in gait recognitionTanawongsuwan, Rawesak 01 December 2003 (has links)
No description available.
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Speech accent identification and speech recognition enhancement by speaker accent adaptation /Tanabian, Mohammad M., January 1900 (has links)
Thesis (M.Sc.) - Carleton University, 2005. / Includes bibliographical references (p. 150-155). Also available in electronic format on the Internet.
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A two-level model-based object recognition technique黃業新, Wong, Yip-san. January 1995 (has links)
published_or_final_version / Computer Science / Master / Master of Philosophy
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High speed auditory analysisGransden, I. R. January 1995 (has links)
No description available.
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Feature extraction for chart pattern classification in financial time seriesZheng, Yue Chu January 2018 (has links)
University of Macau / Faculty of Science and Technology. / Department of Computer and Information Science
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Fast frequent pattern mining.January 2003 (has links)
Yabo Xu. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 57-60). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Frequent Pattern Mining --- p.1 / Chapter 1.2 --- Biosequence Pattern Mining --- p.2 / Chapter 1.3 --- Organization of the Thesis --- p.4 / Chapter 2 --- PP-Mine: Fast Mining Frequent Patterns In-Memory --- p.5 / Chapter 2.1 --- Background --- p.5 / Chapter 2.2 --- The Overview --- p.6 / Chapter 2.3 --- PP-tree Representations and Its Construction --- p.7 / Chapter 2.4 --- PP-Mine --- p.8 / Chapter 2.5 --- Discussions --- p.14 / Chapter 2.6 --- Performance Study --- p.15 / Chapter 3 --- Fast Biosequence Patterns Mining --- p.20 / Chapter 3.1 --- Background --- p.21 / Chapter 3.1.1 --- Differences in Biosequences --- p.21 / Chapter 3.1.2 --- Mining Sequential Patterns --- p.22 / Chapter 3.1.3 --- Mining Long Patterns --- p.23 / Chapter 3.1.4 --- Related Works in Bioinformatics --- p.23 / Chapter 3.2 --- The Overview --- p.24 / Chapter 3.2.1 --- The Problem --- p.24 / Chapter 3.2.2 --- The Overview of Our Approach --- p.25 / Chapter 3.3 --- The Segment Phase --- p.26 / Chapter 3.3.1 --- Finding Frequent Segments --- p.26 / Chapter 3.3.2 --- The Index-based Querying --- p.27 / Chapter 3.3.3 --- The Compression-based Querying --- p.30 / Chapter 3.4 --- The Pattern Phase --- p.32 / Chapter 3.4.1 --- The Pruning Strategies --- p.34 / Chapter 3.4.2 --- The Querying Strategies --- p.37 / Chapter 3.5 --- Experiment --- p.40 / Chapter 3.5.1 --- Synthetic Data Sets --- p.40 / Chapter 3.5.2 --- Biological Data Sets --- p.46 / Chapter 4 --- Conclusion --- p.55 / Bibliography --- p.60
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Shape representation based on wavelet skeletonYou, Xinge 01 January 2004 (has links)
No description available.
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Finding color and shape patterns in imagesCohen, Scott. January 1900 (has links)
Thesis (Ph.D)--Stanford University, 1999. / Title from pdf t.p. (viewed May 9, 2002). "May 1999." "Adminitrivia V1/Prg/19990528"--Metadata.
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